PT - JOURNAL ARTICLE
AU - Belliveau, Nathan M.
AU - Barnes, Stephanie L.
AU - Ireland, William T.
AU - Jones, Daniel L.
AU - Sweredoski, Michael J.
AU - Moradian, Annie
AU - Hess, Sonja
AU - Kinney, Justin B.
AU - Phillips, Rob
TI - Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria
AID - 10.1073/pnas.1722055115
DP - 2018 May 22
TA - Proceedings of the National Academy of Sciences
PG - E4796--E4805
VI - 115
IP - 21
4099 - http://www.pnas.org/content/115/21/E4796.short
4100 - http://www.pnas.org/content/115/21/E4796.full
SO - Proc Natl Acad Sci USA2018 May 22; 115
AB - Organisms must constantly make regulatory decisions in response to a change in cellular state or environment. However, while the catalog of genomes expands rapidly, we remain ignorant about how the genes in these genomes are regulated. Here, we show how a massively parallel reporter assay, Sort-Seq, and information-theoretic modeling can be used to identify regulatory sequences. We then use chromatography and mass spectrometry to identify the regulatory proteins that bind these sequences. The approach results in quantitative base pair-resolution models of promoter mechanism and was shown in both well-characterized and unannotated promoters in Escherichia coli. Given the generality of the approach, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in a wide range of bacteria.Gene regulation is one of the most ubiquitous processes in biology. However, while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here, we take a first step toward multipromoter dissection and show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect multiple bacterial promoters in a systematic way. We show this approach on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases, we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input–output relationships. Given the generality of the approach presented here, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.